diff --git a/sCOCA_ML/models/FNO_models.py b/sCOCA_ML/models/FNO_models.py
index f8234af..2f14198 100644
--- a/sCOCA_ML/models/FNO_models.py
+++ b/sCOCA_ML/models/FNO_models.py
@@ -112,18 +112,16 @@ class FNOBlock3D(nn.Module):
         4. Repeats the steps for the second convolution.
     
     C: Combination:
-        1. Concatenation: Conctenates the outputs from the Fourier and real space blocks (channel size is doubled).
-        2. Final Convolution: Applies a final convolution to reduce the channel size.
-        3. Activation: Applies a ReLU activation function.
-        4. FiLM: Applies Feature-wise Linear Modulation (FiLM) to condition the combined features on style parameters.
-        5. Dropout: Applies dropout to the output tensor.
+        1. Addition: adds the outputs from the Fourier and real space block.
+        2. Activation: Applies a ReLU activation function.
+        3. FiLM: Applies Feature-wise Linear Modulation (FiLM) to condition the combined features on style parameters.
+        4. Dropout: Applies dropout to the output tensor.
     """
     
     def __init__(self, in_channels, out_channels, filtering=None, style_dim=None, dropout=0.05):
         super(FNOBlock3D, self).__init__()
         self.fourier_block = FourierSpaceBlock3D(in_channels, out_channels, filtering=filtering, style_dim=style_dim,)
         self.real_block = RealSpaceBlock3D(in_channels, out_channels, style_dim=style_dim)
-        self.comb_conv = nn.Conv3d(2 * out_channels, out_channels, kernel_size=1, padding=0)
         self.relu = nn.ReLU(inplace=True)
         self.film = FiLM(out_channels, style_dim) if style_dim else None
         self.dropout = nn.Dropout(dropout) if dropout > 0 else None
@@ -131,9 +129,7 @@ class FNOBlock3D(nn.Module):
     def forward(self, x, style=None):
         fourier_out = self.fourier_block(x, style)
         real_out = self.real_block(x, style)
-        combined = torch.cat([fourier_out, real_out], dim=1)
-        out = self.comb_conv(combined)
-        out = self.relu(out)
+        out = self.relu(real_out + fourier_out)
         if self.film is not None:
             out = self.film(out, style)
         if self.dropout is not None: